AI Data Engineer

Title - AI Data Engineer

Type - Contract

Location - Remote

Roles and Responsibilities:

• Develop and maintain robust data pipelines integrating multiple enterprise systems such as SAP, gLIMS, Veeva, MODA, AMPS, and Batch Tracker to ensure reliable data flow and accessibility.
• Design, implement, and optimize Snowflake data models and persistent storage solutions tailored for AI and advanced analytics use cases.
• Build and manage API and event-driven integrations to support real-time agent workflows and processing requirements.
• Implement comprehensive data quality management, data lineage tracking, governance frameworks, and continuous monitoring to maintain data integrity and compliance.
• Enable AI agents and Retrieval-Augmented Generation (RAG) solutions by curating trusted, accessible, and well-governed data assets.
• Ensure all data solutions are secure, scalable, and compliant with organizational policies and industry regulations.
• Collaborate with cross-functional teams including data scientists, analysts, and IT to align data engineering efforts with business objectives.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• 6+ years of hands-on experience in data engineering, with a focus on AI and analytics data infrastructure.
• Proven expertise in Data Modelling, data pipeline development, and ETL processes.
• Strong programming skills in Python for data processing and automation tasks.
• Proficiency in writing and optimizing complex SQL queries.
• Extensive experience working with cloud platforms, especially AWS, including services related to data storage, processing, and security.
• Hands-on experience with Snowflake for data warehousing and scalable data storage solutions.
• Familiarity with API development and event-driven architecture to support real-time data workflows.
• Knowledge of RAG (Retrieval-Augmented Generation) techniques and their data requirements is highly desirable.
• Strong understanding of data governance, data quality frameworks, and compliance standards.
• Excellent problem-solving skills, attention to detail, and ability to work collaboratively in a fast-paced environment.